Breast Imaging Reporting And Data System Score Research Articles

Correlation between radiological imaging and histopathological findings in patients with breast lump

Background: Breast cancer is the most common cancer among women globally and the second leading cause of cancer-related deaths, after lung cancer. Early detection via routine screening is crucial, as not all breast lumps are cancerous and benign lumps do not always progress to cancer. To improve diagnostic accuracy, a triple assessment approach is used, combining radiological imaging, pathological diagnosis, and clinical examination. Techniques such as mammography, ultrasonography, and fine needle aspiration cytology (FNAC) are key to this evaluation. This study assesses the breast imaging reporting and data system (BIRADS) scoring system’s diagnostic accuracy by comparing radiological techniques with histopathological findings. Methods: The study involved 100 patients with breast lumps, categorised into three groups based on BIRADS scores: group A (BIRADS I-III), group B (BIRADS IV), and group C (BIRADS V). Data analysis using chi-square and student’s t tests were done. Results: In our study we found that accuracy of BIRADS score: sensitivity: 88.9%, specificity: 89.5%, positive predictive value: 97.3%, negative predictive value: 65.4% and diagnostic accuracy: 81%. Conclusions: The study demonstrated a high incidence of fibroadenoma (66%), others (3%) as benign cases and invasive ductal carcinoma (31%) malignant cases. The study highlights the importance of accurate diagnosis and targeted screening, especially in high-risk groups such as postmenopausal women and those with a family history of breast cancer. The findings affirm the high sensitivity and specificity of the BIRADS system as a valuable diagnostic tool.

Comparison between BIRAD Scores and Histological features in Diagnosis of Breast Neoplasia at Warith International Cancer Institution.

Introduction: Accurate evaluation and classification of breast lesions using the Breast Imaging-Reporting and Data System (BIRADS) are crucial for appropriate management and treatment planning of breast cancer. This study explores the relationship between BIRADS scores and histological features in the diagnosis of breast neoplasia at the Warith International Cancer Institution in Karbala, Iraq. Methods: This descriptive study included 520 patients diagnosed with breast neoplasia with a pre-diagnostic malignancy probability (BI-RADS 3, 4, or 5) between June 2023 and June 2024. Based on the diagnostic imaging method, patients were classified into mammography and ultrasonography groups. Clinicopathological factors, including age, BI-RADS categories, and histological findings, were analyzed. Results: Mammogram findings revealed that 63.65% of patients had benign results, while 20.77% had findings indicative of malignancy. Ultrasound findings showed that 71.35% of patients had benign results, and 11.35% had findings suggestive of malignancy. Histological analysis indicated that 23.85% of patients had malignant results, 68.07% had benign findings, and 2.31% showed suspicious results. Patients aged 50 years and above had a significantly higher likelihood of detecting malignant breast lesions through mammography compared to younger patients. At the same time, no significant association was found between age groups and ultrasound findings. Conclusion: Mammography demonstrated high sensitivity and specificity in detecting breast neoplasia, although there were false positives and negatives. Ultrasound screening also effectively detected breast abnormalities, particularly in identifying lesions that required further evaluation. The study highlights the importance of age in influencing breast cancer detection through mammography, with older patients having a higher detection rate than younger patients.

Age‑integrated breast imaging reporting and data system assessment model to improve the accuracy of breast cancer diagnosis.

Early diagnosis is an effective strategy for decreasing breast cancer mortality. Ultrasonography is one of the most predominant imaging modalities for breast cancer owing to its convenience and non-invasiveness. The present study aimed to develop a model that integrates age with Breast Imaging Reporting and Data System (BI-RADS) lexicon to improve diagnostic accuracy of ultrasonography in breast cancer. This retrospective study comprised two cohorts: A training cohort with 975 female patients from Renmin Hospital of Wuhan University (Wuhan, China) and a validation cohort with 500 female patients from Maternal and Child Health Hospital of Hubei Province (Wuhan, China). Logistic regression was used to construct a model combining BI-RADS score with age and to determine the age-based prevalence of breast cancer to predict a cut-off age. The model that integrated age with BI-RADS scores demonstrated the best performance compared with models based solely on age or BI-RADS scores, with an area under the curve (AUC) of 0.872 (95% CI: 0.850-0.894, P<0.001). Furthermore, among participants aged <30 years, the prevalence of breast cancer was lower than the lower limit of the reference range (2%) for BI-RADS subcategory 4A lesions but within the reference range for BI-RADS category 3 lesions, as indicated by linear regression analysis. Therefore, it is recommended that management for this subset of participants are categorized as BI-RADS category 3, meaning that biopsies typically indicated could be replaced with short-term follow-up. In conclusion, the integrated assessment model based on age and BI-RADS may enhance accuracy of ultrasonography in diagnosing breast lesions and young patients with BI-RADS subcategory 4A lesions may be exempted from biopsy.

Digital Breast Tomosynthesis for Upgraded BIRADS Scoring towards the True Pathology of Lesions Detected by Contrast-Enhanced Mammography

Objective: To determine the added value of digital breast tomosynthesis (DBT) in the assessment of lesions detected by contrast-enhanced mammography (CEM). Material and methods: A retrospective study was conducted in a tertiary university medical center. All CEM studies including DBT performed between January 2016 and December 2020 were included. Lesions were categorized and scored by four dedicated breast radiologists according to the recent CEM and DBT supplements to the Breast Imaging Reporting and Data System (BIRADS) lexicon. Changes in the BIRADS score of CEM-detected lesions with the addition of DBT were evaluated according to the pathology results and 1-year follow-up imaging study. Results: BIRADS scores of CEM-detected lesions were upgraded toward the lesion’s pathology with the addition of DBT (p &gt; 0.0001), overall and for each reader. The difference in BIRADS scores before and after the addition of DBT was more significant for readers who were less experienced. The reason for changes in the BIRADS score was better lesion margin visibility. The main BIRADS descriptors applied in the malignant lesions were spiculations, calcifications, architectural distortion, and sharp or obscured margins. Conclusions: The addition of DBT to CEM provides valuable information on the enhancing lesion, leading to a more accurate BIRADS score.

A prospective cross-sectional observational comparative study: evaluating palpable breast lumps through comparative analysis of sonomammography breast imaging reporting and data system scores and fine needle aspiration cytology

This study protocol outlines a prospective cross-sectional observational investigation aimed at assessing the correlation between Sonomammography Breast Imaging Reporting and Data System (BI-RADS) scores and Fine-Needle Aspiration Cytology (FNAC) findings in diagnosing benign and malignant palpable breast lumps among patients admitted to AVBRH. The primary objective is to understand the diagnostic accuracy of FNAC and Sonomammography BI-RADS scoring in identifying breast lumps’ nature. Four specific objectives guide this study: 1) To determine the diagnostic accuracy of FNAC; 2) To evaluate the diagnostic precision of Sonomammography BI-RADS scores; 3) To compare the diagnostic outcomes of sonomammography and FNAC with HPE, and 4) To examine the age-wise distribution of benign and malignant palpable breast diseases. The study will be conducted at AVBRH, Sawangi (Meghe), Wardha, over three years, commencing in June 2022. The anticipated findings from this study will significantly contribute to refining the diagnostic strategies for palpable breast lumps, enhancing patient care and decision-making.

Role of Tomosynthesis in Determining the BI-RADS Score of Individuals with Indeterminate Mammography Results

Background: Tomosynthesis, despite its potential to produce superior images compared to mammography for Breast Imaging-Reporting and Data System (BI-RADS) scoring, has not yet been widely adopted. This is likely due to a combination of insufficient data and a scarcity of expertise in this area. Objectives: In this study, we aimed to evaluate the potential benefits of tomosynthesis for patients with indeterminate BI-RADS results from full-field digital mammography (FFDM). Specifically, we sought to determine whether this method could clarify ambiguous BI-RADS scores. Patients and Methods: This cross-sectional study involved 386 female patients, with an average age of 44.7 ± 7.9 years. The study included all patients who were admitted to a referral center for breast radiology during 2019 - 2020 and underwent both FFDM and tomosynthesis within a short interval. The purpose of performing tomosynthesis was to assess its additional benefits over FFDM. The collected data was input into SPSS version 20 for analysis. A P-value of less than 0.05 was deemed statistically significant. Results: Out of 152 patients who initially had indeterminate findings in mammography (BI-RADS score of 0), only one patient (0.7%) remained indeterminate after tomosynthesis. This implies that tomosynthesis was able to clarify the BI-RADS scores for 99.3% of patients with previously indeterminate scores. Specifically, out of these 151 patients, 81 were scored as BI-RADS 2, 45 as BI-RADS 3, 19 as BI-RADS 4, and six as BI-RADS 5. Conclusion: Tomosynthesis has the capability to clarify unclear FFDM BI-RADS scores in over 99% of cases. This suggests that it could serve as the primary supplementary imaging technique for cases with indeterminate BI-RADS scores.

Role of Tomosynthesis in Determining the BI-RADS Score of Individuals with Indeterminate Mammography Results

Background: Tomosynthesis, despite its potential to produce superior images compared to mammography for Breast Imaging-Reporting and Data System (BI-RADS) scoring, has not yet been widely adopted. This is likely due to a combination of insufficient data and a scarcity of expertise in this area. Objectives: In this study, we aimed to evaluate the potential benefits of tomosynthesis for patients with indeterminate BI-RADS results from full-field digital mammography (FFDM). Specifically, we sought to determine whether this method could clarify ambiguous BI-RADS scores. Patients and Methods: This cross-sectional study involved 386 female patients, with an average age of 44.7 ± 7.9 years. The study included all patients who were admitted to a referral center for breast radiology during 2019 - 2020 and underwent both FFDM and tomosynthesis within a short interval. The purpose of performing tomosynthesis was to assess its additional benefits over FFDM. The collected data was input into SPSS version 20 for analysis. A P-value of less than 0.05 was deemed statistically significant. Results: Out of 152 patients who initially had indeterminate findings in mammography (BI-RADS score of 0), only one patient (0.7%) remained indeterminate after tomosynthesis. This implies that tomosynthesis was able to clarify the BI-RADS scores for 99.3% of patients with previously indeterminate scores. Specifically, out of these 151 patients, 81 were scored as BI-RADS 2, 45 as BI-RADS 3, 19 as BI-RADS 4, and six as BI-RADS 5. Conclusion: Tomosynthesis has the capability to clarify unclear FFDM BI-RADS scores in over 99% of cases. This suggests that it could serve as the primary supplementary imaging technique for cases with indeterminate BI-RADS scores.

Exploring the Relationship Between CD 166 Expression and Breast Imaging Reporting and Data System (BI-RADS) Scores in Breast Cancer Patients and Healthy Volunteers.

This research embarked on a crucial endeavor to clarify the connection between levels of CD166 expression and the established Breast Imaging Reporting and Data System (BI-RADS) grading system. Through a comprehensive exploration of this correlation, the objective was to ascertain if CD166 could function as an additional biomarker, enhancing the predictive effectiveness of the BI-RADS classification. This prospective observational study involved 81 women with histopathologically confirmed early breast tumors and 81 radiologically confirmed healthy breast volunteers. The BI-RADS scores of all the participants included in the study were recorded. Before starting treatment, serum, saliva, and urine samples were collected. The CD166 levels were quantified using an enzyme-linked immunosorbent assay. The study involved the analysis and comparison of the mean and standard deviations of CD166 expression in serum, saliva, and urine across various BI-RADS categories. Notably, statistically significant differentiation was found (p=0.00) across all samples spanning the spectrum of BI-RADS categories. A progressive rise in CD166 concentration coincides with the increasing gradient of the BI-RADS category, implying a possible link between CD166 and breast cancer progression and severity.

Knowledge Tensor-Aided Breast Ultrasound Image Assistant Inference Framework.

Breast cancer is one of the most prevalent cancers in women nowadays, and medical intervention at an early stage of cancer can significantly improve the prognosis of patients. Breast ultrasound (BUS) is a widely used tool for the early screening of breast cancer in primary care hospitals but it relies heavily on the ability and experience of physicians. Accordingly, we propose a knowledge tensor-based Breast Imaging Reporting and Data System (BI-RADS)-score-assisted generalized inference model, which uses the BI-RADS score of senior physicians as the gold standard to construct a knowledge tensor model to infer the benignity and malignancy of breast tumors and axes the diagnostic results against those of junior physicians to provide an aid for breast ultrasound diagnosis. The experimental results showed that the diagnostic AUC of the knowledge tensor constructed using the BI-RADS characteristics labeled by senior radiologists achieved 0.983 (95% confidential interval (CI) = 0.975-0.992) for benign and malignant breast cancer, while the diagnostic performance of the knowledge tensor constructed using the BI-RADS characteristics labeled by junior radiologists was only 0.849 (95% CI = 0.823-0.876). With the knowledge tensor fusion, the AUC is improved to 0.887 (95% CI = 0.864-0.909). Therefore, our proposed knowledge tensor can effectively help reduce the misclassification of BI-RADS characteristics by senior radiologists and, thus, improve the diagnostic performance of breast-ultrasound-assisted diagnosis.

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human-machine interactions, but its implications regarding artificial intelligence (AI)-aided mammography reading are unknown. Purpose To determine how automation bias can affect inexperienced, moderately experienced, and very experienced radiologists when reading mammograms with the aid of an artificial intelligence (AI) system. Materials and Methods In this prospective experiment, 27 radiologists read 50 mammograms and provided their Breast Imaging Reporting and Data System (BI-RADS) assessment assisted by a purported AI system. Mammograms were obtained between January 2017 and December 2019 and were presented in two randomized sets. The first was a training set of 10 mammograms, with the correct BI-RADS category suggested by the AI system. The second was a set of 40 mammograms in which an incorrect BI-RADS category was suggested for 12 mammograms. Reader performance, degree of bias in BI-RADS scoring, perceived accuracy of the AI system, and reader confidence in their own BI-RADS ratings were assessed using analysis of variance (ANOVA) and repeated-measures ANOVA followed by post hoc tests and Kruskal-Wallis tests followed by the Dunn post hoc test. Results The percentage of correctly rated mammograms by inexperienced (mean, 79.7% ± 11.7 [SD] vs 19.8% ± 14.0; P < .001; r = 0.93), moderately experienced (mean, 81.3% ± 10.1 vs 24.8% ± 11.6; P < .001; r = 0.96), and very experienced (mean, 82.3% ± 4.2 vs 45.5% ± 9.1; P = .003; r = 0.97) radiologists was significantly impacted by the correctness of the AI prediction of BI-RADS category. Inexperienced radiologists were significantly more likely to follow the suggestions of the purported AI when it incorrectly suggested a higher BI-RADS category than the actual ground truth compared with both moderately (mean degree of bias, 4.0 ± 1.8 vs 2.4 ± 1.5; P = .044; r = 0.46) and very (mean degree of bias, 4.0 ± 1.8 vs 1.2 ± 0.8; P = .009; r = 0.65) experienced readers. Conclusion The results show that inexperienced, moderately experienced, and very experienced radiologists reading mammograms are prone to automation bias when being supported by an AI-based system. This and other effects of human and machine interaction must be considered to ensure safe deployment and accurate diagnostic performance when combining human readers and AI. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Baltzer in this issue.

Comparative study between digital breast tomosynthesis plus digital mammography and digital mammography alone in symptomatic women using BI-RADS score

Background: Digital mammography (DM) is the only screening modality that has been proven to reduce mortality from breast cancer through early detection. However, to reduce false positive results and improve the sensitivity of DM, we undertook a study to compare the impact of digital breast tomosynthesis (DBT) to DM in the evaluation of symptomatic women using the breast imaging reporting and data system (BIRADS) score. Aims and Objectives: The aim of the study was to compare the impact of DBT to DM in the evaluation of symptomatic women using BIRADS score. Materials and Methods: This cross-sectional study of 100 symptomatic patients in the age group of 35–85 years who underwent DM and DBT was included in the study and was analyzed using the American College of Radiology-BIRADS score. Patients with a palpable breast lump, pain, nipple discharge, skin dimpling, or skin changes over breast and nipple inversion or other nipple abnormalities were included in the study. Results: Comparison based on the diagnostic accuracy of mammography alone and mammography plus DBT based on BIRADS score revealed DM had a sensitivity of 96%, specificity of 40.6%, a positive predictive value (PPV) of 72.9% and negative predictive value (NPV) of 86.7% with an accuracy of 75.3% while DM plus DBT had a sensitivity of 98.1%, specificity of 46.9%, the PPV of 75.4%, and NPV of 78.8%. There was no significant increase in sensitivity (P=1.000), specificity (P=0.614), PPV (0.734), and accuracy (0.584). Conclusion: DM plus DBT does not change the BIRADS scoring but its addition increases the diagnostic confidence while there is no significant increase in sensitivity/specificity/PPV/NPV or diagnostic accuracy using DM plus DBT.

The EMory BrEast imaging Dataset (EMBED): A Racially Diverse, Granular Dataset of 3.4 Million Screening and Diagnostic Mammographic Images.

Supplemental material is available for this article. Keywords: Mammography, Breast, Machine Learning © RSNA, 2023.

Performance of breast fine needle aspiration as an initial diagnostic tool: A large academic hospital experience.

The clinical performance of the Yokohama reporting system for breast cytology remains uncertain. In this study, we retrospectively evaluated 318 breast fine needle aspirations (FNABs) from Los Angeles County Hospital over a five-year period, analysing data for breast cytology, histology, and radiology. Among 318 breast FNAB cases, 78.3% (249/318) were benign and 5.3% (17/318) malignant. Of 83 cases with follow-up histology, 14.5% (12/83) were insufficient, 66.3% (55/83) were benign, and 16.9% (17/83) were malignant. Of 55 benign cases, 61.8% (34/55) were fibroadenoma and 9 (9/55, 16.4%) were fibrocystic changes. Two cases were diagnosed as "atypical" but confirmed "benign" on core needle biopsy (CNB). No "suspicious" cases were found. Seventeen malignant cases were confirmed by CNB, including 70.6% (12/17) invasive ductal carcinoma, 11.8% (2/17) invasive lobular carcinoma, and one malignant phyllodes tumour. Receptor studies on cell blocks of three malignant cases showed concordant results with CNB results. In addition, 82.2% (148/180) of lesions with Breast Imaging-Reporting and Data System (BI-RADS) scores of 2 or 3 were benign and 92.3% (12/13) BI-RADS score 5 lesions were malignant on FNAB. Finally, 90% (67/74) of BI-RADS 4a lesions were benign, and 97% (36/37) of fibroadenomas were BI-RADS score 4a. This, by far the largest U.S. breast cytology study, showed 93.3% sensitivity, 100% specificity, 100% positive predictive value, and 98.2% negative predictive value for breast FNAB. Women with breast lesions of BI-RADS score 3 or less have a low risk of malignancy; FNAB would contribute to the reduction of excisional biopsies. FNAB can be considered as an initial diagnostic tool for BI-RADS 4 mass/lesions and satellite lesions, as well as for triaging patients.

Histopathological Correlation of Breast Carcinoma with Breast Imaging-Reporting and Data System.

BackgroundBreast cancer is one of the commonest malignancy cancer worldwide and the Breast Imaging-Reporting and Data System (BI-RADS) classification has been extensively utilised as an adjunct to histopathological examination for malignant breast diseases. This study aims to analyse the concordance between radiological and histopathological findings, demonstrate the high predictive value in the BI-RADS category and evaluate the impact of these findings on surgical intervention and treatment outcome.MethodsThis is a single-centre retrospective study, analysing patients who underwent radiological examination with BI-RADS categories 3, 4 and 5 followed by histopathological examination confirming the diagnosis based on breast core biopsy or excision specimen over 3 years.ResultsA total of 316 specimens from 310 patients were included in this study; 75 cases were categorised BI-RADS 3, 166 as BI-RADS 4 and 75 as BI-RADS 5. Of these, 66 (20.8%) patients in BI-RADS category 3, 82 (25.9%) in BI-RADS category 4 and 5 (1.6%) in BI-RADS category 5 were reported as benign on histopathological examination. Malignant cases were reported in nine (2.8%) cases in BI-RADS category 3, 84 (26.6%) in BI-RADS category 4 and 70 (22.2%) in BI-RADS category 5. The positive predictive value (PPV), negative predictive value (NPV), sensitivity and specificity were 63.9%, 88%, 94.48%, and 43.14%, respectively.ConclusionThere is a significant correlation between BI-RADS score and histopathological results of breast cancer. A higher BI-RADS score is associated with a higher possibility of malignancy (P < 0.001). Our institution’s performance is comparable to other previously published data.

A comprehensive comparison of circulating tumor cells and breast imaging modalities as screening tools for breast cancer in Chinese women.

BackgroundCirculating tumor cells (CTCs) have been recognized as a sensitive biomarker for breast cancer (BC). This study aimed to comprehensively compare CTC with imaging modalities, including ultrasonography, mammography, and contrast-enhanced magnetic resonance imaging (MRI) in screening for BC in Chinese women.MethodsThree hundred forty-three participants were enrolled in this study, including 102 treatment-naive BC patients, 177 with breast benign diseases (BBD) and 64 healthy female patients. All participants underwent CTC testing and at least one of the following examinations, ultrasonography, mammography, and MRI at the Second Affiliated Hospital of Zhejiang University between December 2017 and November 2020. CTCs were quantitatively assessed using cell counting (CTC detection rate/counts) and categorically examined using a cutoff value (CTC classification). The diagnostic power of CTC tests and imaging modalities, including accuracy and capability to predict clinicopathological characteristics of BC, were evaluated and compared.ResultsCTC classification with a cutoff value of 2 showed a “good” diagnostic accuracy of 0.889 for early- to mid-stage BC comparable to breast imaging modalities using Breast Imaging-Reporting and Data System (BI-RADS). MRI demonstrated the highest sensitivity of 0.872 for BC, and CTC classification had the highest specificity of 0.938. A relatively low sensitivity was found for mammography in this cohort of patients. Successful detection of BC by CTC detection rate/counts, but not CTC classification, correlated with two important clinicopathological features, American Joint Committee on Cancer (AJCC) stage and tumor-node-metastasis (TNM) stage. The detection power of certain imaging modalities was also associated with AJCC stage (ultrasonography, p = 0.0438 and MRI, p = 0.0422) and lymph node metastasis (ultrasonography, 0.0157). There were clear correlations between CTC tests (counts or classification) and imaging BI-RADS scoring system in detecting positive BC cases (p < 0.05). Further correlation analysis suggested that CTC quantity, but not CTC classification, had the capability to predict clinicopathological traits of BC that were identified by ultrasonography.ConclusionsCTC tests have a diagnostic potency comparable to breast imaging modalities, and may be used as an alternative screening tool for BC.

Idiopathic granulomatous mastitis: experience at a New York hospital.

Idiopathic granulomatous mastitis (IGM) often mimics breast cancer. Presentation includes pain, palpable mass, suppuration or suspicious imaging. Widely reported in Asia and the Middle East, IGM is diagnosed after excluding specific granulomatous mastitis (SGM). Aetiology remains unknown. Lactation, prolactinaemia, ethnicity, autoimmune disease and Corynebacteria are associated. Treatment is controversial and the prevalence rising. Surgery and non-operative treatments including antibiotics, non-steroidal anti-inflammatory drugs (NSAIDs), steroids, methotrexate and observation have advocates. A retrospective chart review of 63 patients with IGM from 2008 to 2018 was undertaken focusing on birthplace, age, clinical presentation, wound cultures, imaging, treatments and outcomes. Sixty-one of 63 patients were Hispanic; 53 were Mexican-born women aged 23-46. Clinical presentation included pain, painful mass, painless mass, suppuration and abnormal imaging. Some 31/61 ultrasound examinations and 17/33 mammograms were deemed Breast Imaging Reporting and Data System (BI-RADS) score 4 or 5. Management included antibiotics (43), incision and drainage (24), NSAIDs (29), steroids (8), lumpectomy (18) and observation (12). Some 12/20 patients with painless masses resolved with observation, 3 received NSAIDs, 2 received steroids and 3 underwent lumpectomies. Antibiotics resolved 8/43 cases, 5 needed incision and drainage, 26 received NSAIDs, 6 received steroids and 5 underwent lumpectomies. Nineteen patients had indolent disease or recurrence. Excluding malignancy is critical, treatment challenging and recurrence common in IGM. A preponderance of patients were Mexican-born, similar to other reports from the USA. Over 50% of IGM cases had suspicious BI-RADS scores. Best management remains a challenge and ranges from observation to lumpectomy.

Ultrasound high-definition microvasculature imaging with novel quantitative biomarkers improves breast cancer detection accuracy

ObjectivesTo overcome the limitations of power Doppler in imaging angiogenesis, we sought to develop and investigate new quantitative biomarkers of a contrast-free ultrasound microvasculature imaging technique for differentiation of benign from malignant pathologies of breast lesion.MethodsIn this prospective study, a new high-definition microvasculature imaging (HDMI) was tested on 521 patients with 527 ultrasound-identified suspicious breast masses indicated for biopsy. Four new morphological features of tumor microvessels, microvessel fractal dimension (mvFD), Murray’s deviation (MD), bifurcation angle (BA), and spatial vascularity pattern (SVP) as well as initial biomarkers were extracted and analyzed, and the results correlated with pathology. Multivariable logistic regression analysis was used to study the performance of different prediction models, initial biomarkers, new biomarkers, and combined new and initial biomarkers in differentiating benign from malignant lesions.ResultsThe new HDMI biomarkers, mvFD, BA, MD, and SVP, were statistically significantly different in malignant and benign lesions, regardless of tumor size. Sensitivity and specificity of the new biomarkers in lesions > 20 mm were 95.6% and 100%, respectively. Combining the new and initial biomarkers together showed an AUC, sensitivity, and specificity of 97% (95% CI: 95–98%), 93.8%, and 89.2%, respectively, for all lesions regardless of mass size. The classification was further improved by adding the Breast Imaging Reporting and Data System (BI-RADS) score to the prediction model, showing an AUC, sensitivity, and specificity of 97% (95% CI: 95–98%), 93.8%, and 89.2%, respectively.ConclusionThe addition of new quantitative HDMI biomarkers significantly improved the accuracy in breast lesion characterization when used as a complementary imaging tool to the conventional ultrasound.Key Points• Novel quantitative biomarkers extracted from tumor microvessel images increase the sensitivity and specificity in discriminating malignant from benign breast masses.• New HDMI biomarkers Murray’s deviation, bifurcation angles, microvessel fractal dimension, and spatial vascularity pattern outperformed the initial biomarkers.• The addition of BI-RADS scores based on US descriptors to the multivariable analysis using all biomarkers remarkably increased the sensitivity, specificity, and AUC in all size groups.

Correlating Fine Needle Aspiration Cytology Results of Mammary Malignancy with Corresponding Ultrasound BIRADS Score

Objective: Breast mass is a major complaint making women attending any breast clinic. About 10% of the lumps are usually malignant. Triple assessment techniques using clinical examination, ultrasound, and cytology are usually sufficient in reaching the final diagnosis, especially in specialized breast centers. The aim of this study was to assess how accurate ultrasound was in the diagnosis of definite breast cancer according to BIRADS (Breast Imaging Reporting and Data System), and correlate these radiological findings with the results of fineneedle aspiration cytology (FNAC). Methods: A retrospective study included 42 patients who presented with a self-detected breast lump and attending the Early Detection of Breast Tumors clinic in the Oncology Teaching Hospital, Medical City Complex, Baghdad during the period from May 2019 to August 2020. Their age ranged from 29 to 92 years. Patients underwent ultrasound examination after clinical examination and the reported BIRADS score was correlated with the corresponding cytology data. Results: the main ultrasound findings are masses that are either irregular in the majority of cases and this represents 55%, poorly demarcated lesions seen in (26%) while 14% of them were well defined. axillary lymphadenopathy with typical malignant features was noted in (50%). FNAC revealed mammary carcinoma in (93%); while severe atypia was seen in 7%, BIRADS V score was assigned in 76%, of breast exam BIRADS IV in 21% while the remaining 3% were in BIRADS III category. By correlating these ultrasound findings of BIRADS with FNAC results, the ultrasound accuracy in the diagnosis of breast cancer was reaching to 90%. Conclusion: Ultrasonography represents an accurate diagnostic radiological modality for any breast lesion and is thus considered a recommended method for assessment of underlying cause responsible for palpable breast mass or any presenting symptoms related to the breasts. Its value was demonstrated in characterizing the mass lesion, assessing its location, its echo texture, margin, and size, it has a major role in analyzing the axilla for normal or pathological lymph nodes.

The Contribution of a Solid Breast Mass Gray-Scale Histographic Analysis in Ascertaining a Benign-Malignant Differentiation

Objective: The aim of this study was to determine the efficiency of a fat-lesion histographic analysis (FLHA) to make a benign-malignant differentiation, for patients with a breast mass. In addition, it was important to examine the relationship between FLHA rates and Breast Imaging–Reporting and Data System (BI-RADS) scoring. Materials and Methods: This was a retrospective study conducted by examining the breast ultrasonograms (BUS) and histopathologic data of 76 women, having at least one solid breast mass. The patients were grouped according to their histopathologic diagnoses and BUS BI-RADS scores. The recorded digital gray-scale images were transferred to a workstation to quantitatively measure tissue echogenicity. The breast masses and adjacent adipose tissue were evaluated using the ImageJ analysis program, and gray-scale histographic analysis values were generated. The FLHA rate was determined by dividing the fat tissue histographic value by the mass-lesion histographic value. Statistical analysis was performed using this value as well as the patients’ histopathologic data and BUS BI-RADS score. Results: A complementary effect was noted using FLHA rates with the BUS BI-RADS criteria, and a statistically significant difference was detected between benign and malignant histopathology groups ( P &lt; .001). Similarly, the malignant histopathologic diagnosis with BI-RADS 4 and benign histopathologic diagnosis with BI-RADS 4 groups were related ( P &lt; .001). The correlation between BI-RADS criteria and FLHA rates demonstrated a significant difference between BI-RADS 3 and BI-RADS 5 ( P &lt; .001), and BI-RADS 4 and BI-RADS 5 for FLHA rates ( P = .002). Conclusion: It was determined that using the FLHA rate was a complement to the BUS BI-RADS criteria. In this cohort, there was a statistically significant difference in predicting possible malignancy in all BI-RADS classes.

Ultrasound-guided wire localization biopsy in non-palpable breast lesions: predictive factors for malignancy.

The aim of the study was to evaluate the results of ultrasound-guided excisional biopsy in patients with nonpalpable breast lesions and examine factors associated with malignancy. A total of 380 patients who underwent ultrasound-guided excisional biopsy for suspected nonpalpable breast masses, between May 2012 and 2018, were retrospectively examined. Histopathological results of the patients were compared regarding age, ultrasound findings, ultrasonographic and mammographic Breast Imaging Reporting and Data System (BI-RADS) categories and factors predicting malignancy were determined. The mean age of the patients was 48.35 ± 11.23 (17-86) years. There was a history of breast cancer in the families of 22 (5.8%) patients, and 187 (49.2%) patients were in menopause. The complication rate was found to be 6.6%. Malignant lesions were detected in 76 (20%) patients and benign lesions were detected in 304 (79.99%) patients. Some benign lesions were high-risk lesions (16.8%). Most of the patients with malignant lesions had early-stage breast cancer (83.3%). In univariate analyzes, ultrasonographic BI-RADS, mammographic BI-RADS and age variables were found to be associated with malignancy (p = 0.0001). In the multiple logistic regression analysis, ultrasonographic and mammographic BI-RADS values were found to be risk factors for malignancy (p = 0.0001). BI-RADS scoring was used to determine risk factors in predicting malignancy in the evaluation of suspected nonpalpable lesions. The ultrasound-guided wire localization biopsy is a useful method in nonpalpable breast lesions with suspected malignancy that cannot be diagnosed by core/vacuum biopsy or in cases where incompatibility between pathology and radiology results exists.